Google Cloud Pub/Sub vs. Software AG Universal Messaging

If you want to stream high volumes of data, be it for ETL streaming or event sourcing, Google Cloud Pub/Sub is your go-to tool. It's easy to learn, easy to observe its metrics and scales with ease without additional configuration so if you have more producers of consumers, all you need to do is to deploy on k8s your solutions so that you can perform autoscaling on your pods to adjust to the data volume. The DLQ is also very transparent and easy to configure. Your code will have no logic whatsoever regarding orchestrating pubsub, you just plug and play. However, if you are not in the Google Cloud Pub/Sub environment, you might have trouble or be most likely unable to use it since I think it's a product of Google Cloud.

Software AG Universal Messaging is best used in conjunction with Software AG webMethods integration platform, as it works seamlessly with other components of that platform such as webMethods Integration Server and webMethods Trading Networks. It can be used with any messaging client developed in Java or .NET and supports JMS clients, however, it is best suited to being used as one component in an organization that is going to implement the entire webMethods platform to implement their Enterprise Service Bus integration solution.

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• With a pub/sub architecture the consumer is decoupled in time from the publisher i.e. if the consumer goes down, it can replay any events that occurred during its downtime.
• It also allows consumer to throttle and batch incoming data providing much needed flexibility while working with multiple types of data sources
• A simple and easy to use UI on cloud console for setup and debugging
• It enables event-driven architectures and asynchronous parallel processing, while improving performance, reliability and scalability

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• Low latency high performance messaging and event handling
• High availability
• Horizontal scalability
• Seamless integration with Software AG webMethods integration platform

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• Would be nice if the queue could be extended beyond 7 days.
• We found it a bit tricky replay unacknowledged messages when needed.

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• Logging
• Administration
• Observability

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It serves all of our purposes in the most transparent way I can imagine, after seeing other message queueing providers, I can only attest to its quality.

It is easy to create Google Cloud Pub/Sub topics from both Web Console and CLI commands.

Google Cloud Pub/Sub supports creation of one or more subscriptions.

By supporting a BigQuery Pub/Sub subscription to automatically write to a BigQuery table it simplifies development by avoiding implementation of a custom micro service for writes to BigQuery.

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I have never faced a single problem in 4 years.

It's very fast, can be even better if you use protobuf.

They have decent documentation, but you need to pay for support. We weren't able to answer all our questions with the documentation and didn't have time to setup support before we needed it so I can't give it a higher rating but I think it tends to be a bit slow unless you're a GCP enterprise support customer.

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Having used Amazon Web Services SNS & SQS I can say that even if the latter may offer more features, Google Cloud Pub/Sub is easier to use. On the other hand, usage of SNS & SQS as well as documentation and troubleshooting is easier with the AWS solution. Since we are not using GCP only for Pub/Sub the choice depends on other variables.

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Software AG Universal Messaging has excellent performance characteristics, a good high availability story, and works great when you are using the other products in the Software AG webMethods integration platform, as our organization is. It has relatively high licensing costs, which is a large negative when compared with open-source solutions such as Apache Kafka. However, Software AG provides good support services, and is a market leader in the integration space, giving some surety for risk-averse organizations that if something goes wrong we have a vendor we can rely on to help fix it.

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You can just plug in consumers at will and it will respond, there's no need for further configuration or introducing new concepts. You have a queue, if it's slow, you plug in more consumers to process more messages: simple as that.

• Increased Efficiency with reliable and Google managed services up all the time wit Disaster Recovery in place as well
• Definitely Lower costs being a cloud based solution and easier to setup
• Faster Project delivery and go to market plan for the business use cases basis this technology at the back end

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• Enables disparate software systems to be integrated, reducing manual data entry
• Enables high performance event handling for data lakes and analytics
• Has relatively high licensing costs

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